docker6 min read
Dockerfile Optimization — Smaller, Faster Images
Optimize Dockerfiles for faster builds and smaller images using layer caching, multi-stage builds, and Alpine Linux.
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Optimization
17 articles
docker6 min read
Docker Multi-Stage Builds — Reduce Image Size
Master multi-stage Docker builds to reduce image sizes by separating build and runtime stages.
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lora5 min read
LoRA and QLoRA — Efficient LLM Fine-tuning
Master LoRA and QLoRA for efficient fine-tuning of large language models on consumer hardware.
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prompt-engineering4 min read
LLM Prompt Engineering — Advanced Techniques
Master advanced prompt engineering techniques to maximize LLM performance.
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dspy1 min read
DSPy — Programming LLMs Systematically
Systematic programming of LLMs with DSPy framework.
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react2 min read
React Performance — memo, useMemo, useCallback
Optimize React performance with memoization techniques.
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nodejs1 min read
Node.js Performance — Profiling and Optimization
Optimize Node.js applications. Profiling tools, memory management, and performance best practices.
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inference9 min read
LLM Inference Optimization — Quantization, Speculative Decoding, and KV Cache
Optimize LLM inference speed by 10×. Master quantization tradeoffs, speculative decoding, KV cache management, flash attention, and batching strategies.
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api10 min read
API Response Optimization — Compression, Streaming, and Payload Minimization
Reduce API payload sizes and latency through compression, streaming, pagination, and field selection. Master bandwidth optimization for global users.
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performance8 min read
The Backend Performance Checklist for 2026 — From Database to Edge
A comprehensive performance checklist across all layers—database, application, caching, network, and edge.
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database9 min read
Database Query Optimization — EXPLAIN ANALYZE, Indexes, and Rewriting Slow Queries
Master Postgres query optimization using EXPLAIN ANALYZE, covering index types, query rewriting, and plan analysis for production databases.
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llm9 min read
Self-Hosting LLMs With vLLM — Running Open-Source Models in Production
Deploy open-source LLMs at scale with vLLM. Compare frameworks, optimize GPU memory, quantize models, and run cost-effective inference in production.
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prompts7 min read
Prompt Optimization — Automatic and Manual Techniques to Improve LLM Performance
Techniques for manually and automatically optimizing prompts including structured templates, chain-of-thought, few-shot selection, compression, and DSPy automation.
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qdrant7 min read
Qdrant in Production — Collections, Quantization, and Filtering at Scale
Master Qdrant collections, payload filtering, quantization for cost savings, batch operations, and backup strategies for production AI systems.
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RAG10 min read
RAG Chunking Strategies — How You Split Documents Changes Everything
Explore chunking strategies from fixed-size to semantic splitting, including sentence-window retrieval and late chunking techniques that dramatically improve retrieval quality.
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dsa2 min read
Tiling and Splitting Problems: Backtracking meets DP
Solve tiling (domino, triomino) and optimal string splitting problems combining backtracking insight with DP optimization.
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dsa2 min read
Mock Week 2 — Medium Problems with Optimization Round
Week 2 mock: solve medium problems then optimize. Practice the full interview loop of brute force → optimal → follow-up questions. Includes common interviewer follow-up prompts.
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